#!/usr/bin/env python
# -*- coding: utf-8 -*-

# Copyright 2021 Tianmian Tech. All Rights Reserved.
# 
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# 
#     http://www.apache.org/licenses/LICENSE-2.0
# 
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# Copyright 2019 The FATE Authors. All Rights Reserved.
# 
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# 
#     http://www.apache.org/licenses/LICENSE-2.0
# 
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.



import unittest

import numpy as np

from kernel.optimizer import activation


class TestConvergeFunction(unittest.TestCase):
    def test_numeric_stability(self):
        x_list = np.linspace(-709, 709, 10000)

        # Original function
        # a = 1. / (1. + np.exp(-x))
        for x in x_list:
            a1 = 1. / (1. + np.exp(-x))
            a2 = activation.sigmoid(x)
            self.assertTrue(np.abs(a1 - a2) < 1e-5)


if __name__ == '__main__':
    unittest.main()
